Ubiquitin Dynamics in Complexes Reveal Molecular Recognition Mechanisms Beyond Induced Fit and Conformational Selection

Protein-protein interactions play an important role in all biological processes. However, the principles underlying these interactions are only beginning to be understood. Ubiquitin is a small signalling protein that is covalently attached to different proteins to mark them for degradation, regulate transport and other functions. As such, it interacts with and is recognised by a multitude of other proteins. We have conducted molecular dynamics simulations of ubiquitin in complex with 11 different binding partners on a microsecond timescale and compared them with ensembles of unbound ubiquitin to investigate the principles of their interaction and determine the influence of complex formation on the dynamic properties of this protein. Along the main mode of fluctuation of ubiquitin, binding in most cases reduces the conformational space available to ubiquitin to a subspace of that covered by unbound ubiquitin. This behaviour can be well explained using the model of conformational selection. For lower amplitude collective modes, a spectrum of zero to almost complete coverage of bound by unbound ensembles was observed. The significant differences between bound and unbound structures are exclusively situated at the binding interface. Overall, the findings correspond neither to a complete conformational selection nor induced fit scenario. Instead, we introduce a model of conformational restriction, extension and shift, which describes the full range of observed effects.     

A Unified Conformational Selection and Induced Fit Approach to Protein-Peptide Docking

Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II), flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.     

From Induced Fit to Conformational Selection: A Continuum of Binding Mechanism Controlled by the Timescale of Conformational Transitions

In receptor-ligand binding, a question that generated considerable interest is whether the mechanism is induced fit or conformational selection. This question is addressed here by a solvable model, in which a receptor undergoes transitions between active and inactive forms. The inactive form is favored while unbound but the active form is favored while a ligand is loosely bound. As the active-inactive transition rates increase, the binding mechanism gradually shifts from conformational selection to induced fit. The timescale of conformational transitions thus plays a crucial role in controlling binding mechanisms.     

p300/CBP/p53 interaction and regulation of the p53 response.

Substantial evidence points to a critical role for the p300/CREB binding protein (CBP) coactivators in p53 responses to DNA damage. p300/CBP and the associated protein P/CAF bind to and acetylate p53 during the DNA damage response, and are needed for full p53 transactivation as well as downstream p53 effects of growth arrest and/or apoptosis. Beyond this simplistic model, p300/CBP appear to be complex integrators of signals that regulate p53, and biochemically, the multipartite p53/p300/CBP interaction is equally complex. Through physical interaction with p53, p300/CBP can both positively and negatively regulate p53 transactivation, as well as p53 protein turnover depending on cellular context and environmental stimuli, such as DNA damage.     

Intrinsic noise and Hill dynamics in the p53 system

The p53 feedback loop can induce cellular senescence, cell cycle arrest and apoptosis in response to various stresses, including DNA damage, hypoxia and nutrient deprivation. Using a stochastic model of the negative feedback circuit involving p53 and its inhibitor Mdm2, we present the different oscillatory dynamics at the single-cell and population-cell levels as described in the experiments, and the resonant nature of the oscillations is captured. The stationary distributions of protein populations are characterized by non-Gaussian nature which is due to the interplay between time delay and nonlinearity of reactions.     

Regulation of Lef-mediated transcription and p53-dependent pathway by associating beta-catenin with CBP/p300

CBP and its homologue p300 play significant roles in cell differentiation, cell cycle, and anti-oncogenesis. We demonstrated that beta-catenin, recently known as a potent oncogene, and CBP/p300 are associated through its CH3 region, which is a primary target of adenoviral oncoprotein E1A and various nuclear proteins, such as p53, cyclin E, and AP-1, and both are colocalized in the nuclear bodies. CBP/p300 potentiated Lef-mediated transactivation of beta-catenin, and E1A, a potent inhibitor of CBP/p300, repressed its transactivation. Furthermore, overexpression of stable beta-catenin mutant competitively suppressed the p53-dependent pathway. These may be a key mechanism of beta-catenin involved in oncogenic events underlying disruption of tumor suppressor function through CBP/p300.     

Recognition of cisplatin-damaged DNA by p53 protein: critical role of the p53 C-terminal domain

It was shown previously that the p53 protein can recognize DNA modified with antitumor agent cisplatin (cisPt-DNA). Here, we studied p53 binding to the cisPt-DNA using p53 deletion mutants and via modulation of the p53-DNA binding by changes of the protein redox state. Isolated p53 C-terminal domain (CTD) bound to the cisPt-DNA with a significantly higher affinity than to the unmodified DNA. On the other hand, p53 constructs involving the core domain but lacking the C-terminal DNA binding site (CTDBS) exhibited only small binding preference for the cisPt-DNA. Oxidation of cysteine residues within the CD of posttranslationally unmodified full length p53 did not affect its ability to recognize cisPt-DNA. Blocking of the p53 CTDBS by a monoclonal antibody Bp53-10.1 resulted in abolishment of the isolated CTD binding to the cisPt-DNA. Our results demonstrate a crucial role of the basic region of the p53 CTD (aa 363-382) in the cisPt-DNA recognition.     

Managing for Interactions between Local and Global Stressors of Ecosystems

Global stressors, including climate change, are a major threat to ecosystems, but they cannot be halted by local actions. Ecosystem management is thus attempting to compensate for the impacts of global stressors by reducing local stressors, such as overfishing. This approach assumes that stressors interact additively or synergistically, whereby the combined effect of two stressors is at least the sum of their isolated effects. It is not clear, however, how management should proceed for antagonistic interactions among stressors, where multiple stressors do not have an additive or greater impact. Research to date has focussed on identifying synergisms among stressors, but antagonisms may be just as common. We examined the effectiveness of management when faced with different types of interactions in two systems – seagrass and fish communities – where the global stressor was climate change but the local stressors were different. When there were synergisms, mitigating local stressors delivered greater gains, whereas when there were antagonisms, management of local stressors was ineffective or even degraded ecosystems. These results suggest that reducing a local stressor can compensate for climate change impacts if there is a synergistic interaction. Conversely, if there is an antagonistic interaction, management of local stressors will have the greatest benefits in areas of refuge from climate change. A balanced research agenda, investigating both antagonistic and synergistic interaction types, is needed to inform management priorities.     

p53 at the crossroads between cancer and neurodegeneration

Aging, dementia, and cancer share a critical set of altered cellular functions in response to DNA damage, genotoxic stress, and other insults. Recent data suggest that the molecular machinery involved in maintaining neural function in neurodegenerative disease may be shared with oncogenic pathways. Cancer and neurodegenerative diseases may be influenced by common signaling pathways regulating the balance of cell survival versus death, a decision often governed by checkpoint proteins. This paper focuses on one such protein, p53, which represents one of the most extensively studied proteins because of its role in cancer prevention and which, furthermore, has been recently shown to be involved in aging and Alzheimer disease (AD). The contribution of a conformational change in p53 to aging and neurodegenerative processes has yet to be elucidated. In this review we discuss the multiple functions of p53 and how these correlate between cancer and neurodegeneration, focusing on various factors that may have a role in regulating p53 activity. The observation that aging and AD interfere with proteins controlling duplication and cell cycle may lead to the speculation that, in senescent neurons, aberrations in proteins generally dealing with cell cycle control and apoptosis could affect neuronal plasticity and functioning rather than cell duplication.     

Correlation between p53 gene mutations and p53 protein accumulation evaluated by different methodologies

Mutations in the p53 gene are the most common genetic alterations in many tumour histotypes. Many of these mutations induce conformational changes resulting in p53 protein stabilisation and consequently an accumulation detectable with immunochemical methods. Available data on the correlation between p53 gene alterations and p53 overexpression widely vary. In this study we analysed the correlation between p53 gene alterations detected by DGGE, SSCP and sequencing and protein expression detected by flow cytometric and immunohistochemical approaches by using PAb 1801 antibody. The study was performed on 21 bladder tumours and 10 cell lines derived from different tumour histotypes as representative of different methodologic problems which can be met starting from different types of biological material. The best correlation (81%) was observed between p53 mutations and FCM results, using a double evaluation criterion for the latter which includes the percentage of positive cells and "delta values", evaluated as the difference between the mean values of Pab 1801 stained cells and isotypic control. The high correlation obtained between results from this FCM double criterion and p53 gene mutations is a good starting point for the analysis on large series of tumours and for a multiparameter FCM analysis including p53 protein levels.